There once was a group of executives from a highly successful technology company on retreat. You all know this kind of off-site meeting - usually organized by the human resources or marketing types - they often include adventure/survival type games as team building exercises. On this particular retreat, one task put to the executives was particularly challenging. In the middle of a wooded area stood a 15 foot wall. The challenge was to devise a method to get the whole group over the wall using only themselves and materials they could find in the woods nearby. They immediately set to work by brainstorming ideas. These were evaluated one at a time, and after evaluating all of them, the most promising idea was selected based on the thoughtful analysis of the team. They then developed a plan to implement the idea, assigning roles and responsibilities. Once everyone knew what they had to do individually, they executed their plan, and everyone got over the wall. They worked marvelously as a team, and their well thought out plan worked as anticipated. A smashing success, and a good time had by all.
Unfortunately, while they were successful, they were not the most successful at this challenge. It so happened that earlier that week a group of grade school kids (also on a retreat) had also gotten themselves over the wall, but in less time! Their method: someone would yell out an idea. They would try it, and when it did not work, someone would shout out another idea. They would then try that, and so on until finally one of the ideas actually worked and everyone got over the wall.
Ironically, I heard this story at a corporate retreat! In my case, it was many years ago, but I am quite sure many of you may have been told a similar story. It speaks to the dichotomy between massive trial and error and the typical analyze, forecast, plan and execute approach we usually use at work. I was reminded of this story recently when reading Nassim Taleb’s The Black Swan: The Impact of the Highly Improbable. In this book, Taleb argues that many (if not most) real world phenomena have more in common with black swans than bell curve distributions. If we have never seen a black swan, we assume all swans are white. We forecast and plan based on this assumption and it all goes to hell when one single black swan shows up. For example, it’s hard to think anyone could have forecast the emergence and popularity of the iPod. It’s a black swan - not predictable, but world changing. How do we create our own black swans? Since we cannot plan it we are left with massive trial and error.
This was reinforced for me last week when Garr Reynolds’ excellent blog Presentation Zen highlighted Tim Brown’s presentation on Play at TED where he discusses the virtues of quantity (of ideas) and massive experimentation (what he calls "play"):
How many great products came about because someone was "playing around" with something, or some idea? Probably the majority of them. As Taleb points out, if we could forecast the next great thing, we would be doing that next great thing now!
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Unfortunately, while they were successful, they were not the most successful at this challenge. It so happened that earlier that week a group of grade school kids (also on a retreat) had also gotten themselves over the wall, but in less time! Their method: someone would yell out an idea. They would try it, and when it did not work, someone would shout out another idea. They would then try that, and so on until finally one of the ideas actually worked and everyone got over the wall.
Ironically, I heard this story at a corporate retreat! In my case, it was many years ago, but I am quite sure many of you may have been told a similar story. It speaks to the dichotomy between massive trial and error and the typical analyze, forecast, plan and execute approach we usually use at work. I was reminded of this story recently when reading Nassim Taleb’s The Black Swan: The Impact of the Highly Improbable. In this book, Taleb argues that many (if not most) real world phenomena have more in common with black swans than bell curve distributions. If we have never seen a black swan, we assume all swans are white. We forecast and plan based on this assumption and it all goes to hell when one single black swan shows up. For example, it’s hard to think anyone could have forecast the emergence and popularity of the iPod. It’s a black swan - not predictable, but world changing. How do we create our own black swans? Since we cannot plan it we are left with massive trial and error.
This was reinforced for me last week when Garr Reynolds’ excellent blog Presentation Zen highlighted Tim Brown’s presentation on Play at TED where he discusses the virtues of quantity (of ideas) and massive experimentation (what he calls "play"):
How many great products came about because someone was "playing around" with something, or some idea? Probably the majority of them. As Taleb points out, if we could forecast the next great thing, we would be doing that next great thing now!
ShareThis